Chad Gordon
*blue is won matches, orange is lost matches - matchid is chronolnogical from start (1) to end of season (39)* So the other evening, I was starting to draw up my first practice of the 2019-2020 season for the Bay 16-1s. It's a team that has great potential, some fantastic athletes, good height, and just... Continue Reading →
Because I'm on a roll with the R Shiny web app stuff, I figured I'd make another. This one allows you to look at how each player is trending throughout the season in their serve, receive, or attacking stats. Harker - Serve/Rec/Atk Efficiency!! For serving, we look at the outcome of the serve (different reception... Continue Reading →
So. Made my first Shiny web app using R and feeling pretty good right now. It's not sexy by any means - and really only displays 4 different plots that are pre-made, but it's still super cool compared to the absolutely nothing I had built before this. You can check it out by clicking here: Harker... Continue Reading →
Haven't posted anything in a while, so thought I'd throw out an update on the Harker season as we've played about 70% of our matches so far. For those who aren't familiar with Efficiency Change, it is the idea of looking at the result you get, minus the input/the hand you were dealt. For attacking,... Continue Reading →
Played one of the stronger teams in Northern California in Branham HS last night - formerly known as the Bruin Dream back when it was captained by Taylor Averill, Ryan Holmes, and Ryan Sullivan of the CCS championship 2010 class. But for our sake, just wanted to share some real world data from the 2019... Continue Reading →
So, this season at Harker, I convinced my AD to splurge a little and get us Volleymetrics for the spring. I'm stoked to finally get some coded data on the high school level that can hopefully inform my approach to coaching similarly skilled teams in the future - while also validating or disproving some of... Continue Reading →
I've noticed that someone with a lot of nerdy friends who like volleyball has linked my original Attacking Theory post on FB, so I figured I'd give you folks a little extra look on some data from this season. It's just a snapshot, but it's a pretty clean look at how these numbers get computed. This... Continue Reading →
Attacking is a little harder to nail down. The complexity outweighs serving & receiving, making honing in on the best approach very time-consuming. Here's where I've landed: The input for attacking is really the tough one - what factors help predict whether an attacker will be successful or not? In my experimentation, I've looked at... Continue Reading →
We treat serve receive in the same manner we handle serving. We identify the expectations and then quantify the results appropriately. In this case, we break down expectations in FBSO efficiency by conference. We look at how well teams in each conference do when receiving serve (with service errors removed, as these are not really... Continue Reading →
